The Phi-Sat-1 represents one of Europe's first artificial intelligence in space. The main task of the AI chip is to comb through huge sets of images (which will be used for the monitoring of vegetation changes and water quality) and filter out the ones of low quality due to cloud coverage. The AI chip will process large amounts of data which otherwise would be sent for processing on Earth. The main advantage is that the on-board processing makes the delivery more efficient as the "cloudy" images have already been removed. The AI cloud detection experiment is aimed at validating the performance of the on-board inference engine based on a machine learning algorithm for cloud detection. The inference engine runs on a VPU embedded in the
hyperspectral instrument and it will reduce the content of the downloaded data. One of the key issues for hyperspectral instruments in small satellite missions is to simultaneously lower costs while respecting on-board resources (power, mass, etc.) and at the same time to maximize the relevant information to be downlinked by the Ground Segment. Hyperspectral missions typically produced big amounts of information from the observed scenes, such as land, water and ice observations, but sometimes the data cannot be exploited due to the presence of clouds. For instance, more than 30% of the images in Sentinel-2 are cloudy. == Launch ==